Low Cost and High Accuracy Data Gathering in WSNs with Matrix Completion

doi:10.1109/TMC.2017.2775230

CORC > 计算技术研究所 > 中国科学院计算技术研究所 > 中国科学院计算技术研究所期刊论文 > 英文

	Low Cost and High Accuracy Data Gathering in WSNs with Matrix Completion
	Xie, Kun 2,3; Wang, Lele 2; Wang, Xin 1; Xie, Gaogang 4; Wen, Jigang 4
刊名	IEEE TRANSACTIONS ON MOBILE COMPUTING
	2018-07-01
卷号	17 期号:7 页码:1595-1608
关键词	Sparse data gathering matrix completion wireless sensor network
ISSN号	1536-1233
DOI	10.1109/TMC.2017.2775230
英文摘要	Matrix completion has emerged very recently and provides a new venue for low cost data gathering in Wireless Sensor Networks (WSNs). Existing schemes often assume that the data matrix has a known and fixed low-rank, which is unlikely to hold in a practical system for environment monitoring. Environmental data vary in temporal and spatial domains. By analyzing a large set of weather data collected from 196 sensors in ZhuZhou, China, we reveal that weather data have the features of low-rank, temporal stability, and relative rank stability. Taking advantage of these features, we propose an on-line data gathering scheme based on matrix completion theory, named MC-Weather, to adaptively sample different locations according to environmental and weather conditions. To better schedule sampling process while satisfying the required reconstruction accuracy, we propose several novel techniques, including three sample learning principles, an adaptive sampling algorithm based on matrix completion, and a uniform time slot and cross sample model. With these techniques, our MC-Weather scheme can collect the sensory data at required accuracy while largely reducing the cost for sensing, communication, and computation. We perform extensive simulations based on the data traces from weather monitoring and the simulation results validate the efficiency and efficacy of the proposed scheme.
资助项目	National Natural Science Foundation of China[61572184] ; National Natural Science Foundation of China[61725206] ; National Natural Science Foundation of China[61472130] ; National Natural Science Foundation of China[61472131] ; Hunan Provincial Natural Science Foundation of China[2017JJ1010] ; US National Science Foundation[ECCS 1408247] ; US National Science Foundation[CNS 1526843] ; US National Science Foundation[ECCS 1731238] ; Foundation of Key Laboratory of Machine Intelligence and Advanced Computing of the Ministry of Education[MSC-201708A] ; Science and Technology Key Projects of Hunan Province[2015TP1004] ; outstanding graduate student innovation fund program of collaborative innovation center of high performance computing
WOS研究方向	Computer Science ; Telecommunications
语种	英语
出版者	IEEE COMPUTER SOC
WOS记录号	WOS:000434291500008
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/5271]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Xie, Kun
作者单位	1.SUNY Stony Brook, Dept Elect & Comp Engn, Stony Brook, NY 11794 USA 2.Hunan Univ, Coll Comp Sci & Elect Engn, Changsha 410082, Hunan, Peoples R China 3.Sun Yat Sen Univ, Minist Educ, Key Lab Machine Intelligence & Adv Comp, Guangzhou 510000, Guangdong, Peoples R China 4.Chinese Acad Sci, Inst Comp Technol, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Xie, Kun,Wang, Lele,Wang, Xin,et al. Low Cost and High Accuracy Data Gathering in WSNs with Matrix Completion[J]. IEEE TRANSACTIONS ON MOBILE COMPUTING,2018,17(7):1595-1608.
APA	Xie, Kun,Wang, Lele,Wang, Xin,Xie, Gaogang,&Wen, Jigang.(2018).Low Cost and High Accuracy Data Gathering in WSNs with Matrix Completion.IEEE TRANSACTIONS ON MOBILE COMPUTING,17(7),1595-1608.
MLA	Xie, Kun,et al."Low Cost and High Accuracy Data Gathering in WSNs with Matrix Completion".IEEE TRANSACTIONS ON MOBILE COMPUTING 17.7(2018):1595-1608.